Traditionally, a student driver wanting to obtain a drivers' license may take driving classes and/or participate in various driving sessions whereby the student is evaluated on his driving performance. During a typical driving session, a student driver may be requested to drive along a certain route while the student's driving skills are observed and evaluated by an instructor. Based on the instructor's observations, the student driver is graded according to a set of criteria.
To improve the efficiency and objectivity of the driver testing process, typical systems may incorporate other sources of data collection in addition to the driver's observations. Using various data collection techniques, one or more computers and/or sensors in the vehicle may record data throughout a driving session. The instructor may then use a report generated from this data to provide feedback to the student and/or to evaluate the student's driving skills.
In spite of these additional sources of data collection, the instructor's role in determining the student's driving skills remains an important part of the performance evaluation process, since not all driver activity can be recorded with computer-based systems. Although an instructor may utilize automated processing techniques on the collected data to quickly generate the report, these automated processes do not typically allow a driving instructor to supplement or otherwise add her own comments to the report. As a result, a driving instructor's observations may not be reflected in any feedback provided to the student driver. Therefore, providing efficient and accurate feedback to student drivers that incorporates a driving instructor's observations presents several challenges.